
Cloud Vulnerability DB
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CVE-2022-48674 is a use-after-free vulnerability discovered in the Linux kernel's EROFS (Enhanced Read-Only File System) implementation. The vulnerability was disclosed on May 3, 2024, affecting Linux kernel versions from 4.19.26 through 5.19.9 and specific 6.0 release candidates. The issue occurs specifically on uni-processor (UP) platforms when CONFIG_SMP is disabled, where erofs_workgroup_unfreeze() fails to properly reset to orig_val, causing a race condition where the pcluster is reused unexpectedly before being freed (NVD, Red Hat).
The vulnerability is caused by a race condition in the EROFS filesystem's workgroup handling code. During stress testing with CONFIG_SMP disabled, KASAN reported a use-after-free condition in __mutex_lock, specifically reading 8 bytes at address ffff8881094223f8. The root cause was identified in the erofs_workgroup_unfreeze() function, which failed to reset to orig_val, leading to unexpected pcluster reuse before proper deallocation. The vulnerability has been assigned a CVSS v3.1 base score of 7.8 (HIGH) with vector CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H (NVD).
The vulnerability can lead to memory corruption or system crashes due to the use-after-free condition in the kernel's memory management. This primarily affects systems running on uni-processor platforms with CONFIG_SMP disabled, which are relatively rare in modern deployments (Red Hat).
The vulnerability requires local access and can be triggered during stress testing conditions on affected systems. It specifically affects systems with CONFIG_SMP disabled, which limits its potential impact as most modern systems run with SMP enabled (Kernel Patch).
The issue has been resolved by removing the UP-specific code path entirely, as UP platforms are now rare. The fix involves dropping the specific-designed path for UP platforms in the EROFS implementation. The patch has been merged into the Linux kernel, and affected distributions have released updates (Kernel Patch).
Source: This report was generated using AI
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